UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results

This paper is the report of the first Under-Display Camera (UDC) image restoration challenge in conjunction with the RLQ workshop at ECCV 2020. The challenge is based on a newly-collected database of Under-Display Camera. The challenge tracks correspond to two types of display: a 4k Transparent OLED...

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Hauptverfasser: Zhou, Yuqian, Kwan, Michael, Tolentino, Kyle, Emerton, Neil, Lim, Sehoon, Large, Tim, Fu, Lijiang, Pan, Zhihong, Li, Baopu, Yang, Qirui, Liu, Yihao, Tang, Jigang, Ku, Tao, Ma, Shibin, Hu, Bingnan, Wang, Jiarong, Puthussery, Densen, S, Hrishikesh P, Kuriakose, Melvin, CV, Jiji, Sundar, Varun, Hegde, Sumanth, Kothandaraman, Divya, Mitra, Kaushik, Jassal, Akashdeep, Shah, Nisarg A, Nathan, Sabari, Rahel, Nagat Abdalla Esiad, Chen, Dafan, Nie, Shichao, Yin, Shuting, Ma, Chengconghui, Wang, Haoran, Zhao, Tongtong, Zhao, Shanshan, Rego, Joshua, Chen, Huaijin, Li, Shuai, Hu, Zhenhua, Lau, Kin Wai, Po, Lai-Man, Yu, Dahai, Rehman, Yasar Abbas Ur, Li, Yiqun, Xing, Lianping
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Sprache:eng
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Zusammenfassung:This paper is the report of the first Under-Display Camera (UDC) image restoration challenge in conjunction with the RLQ workshop at ECCV 2020. The challenge is based on a newly-collected database of Under-Display Camera. The challenge tracks correspond to two types of display: a 4k Transparent OLED (T-OLED) and a phone Pentile OLED (P-OLED). Along with about 150 teams registered the challenge, eight and nine teams submitted the results during the testing phase for each track. The results in the paper are state-of-the-art restoration performance of Under-Display Camera Restoration. Datasets and paper are available at https://yzhouas.github.io/projects/UDC/udc.html.
DOI:10.48550/arxiv.2008.07742